Eye prediction of digital driver with power distribution network noise

Chiu Chih Chou, Hao Hsiang Chuang, Tzong Lin Wu, Shih Hung Weng, Chung Kuan Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

Algorithms featuring fast and accurate estimation of worst-case eye diagram have been proposed to replace the time-consuming random bit simulation in channel design. However, when the interaction between nonlinear I/O circuits and power distribution network (PDN) noise is included, most of those approaches fail to maintain accuracy. Based on the superposition of multiple bit pattern responses (SMBP) concept, Ren and Oh [1] developed an algorithm to fast predict the eye diagram that theoretically captures any nonlinearity in the circuit. In this paper, a test circuit with PDN was constructed to examine the performance of this algorithm. The experiment results show good agreement with the results simulated by long PRBS in HSPICE.

Original languageEnglish
Title of host publication2012 IEEE 21st Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2012
Pages131-134
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE 21st Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2012 - Tempe, AZ, United States
Duration: 21 Oct 201224 Oct 2012

Publication series

Name2012 IEEE 21st Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2012

Conference

Conference2012 IEEE 21st Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2012
Country/TerritoryUnited States
CityTempe, AZ
Period21/10/1224/10/12

Keywords

  • eye diagram
  • multiple bit pattern response
  • nonlinear effect
  • power distribution network
  • worst case estimation algorithm

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